IEEE Trans Med Imaging. 2022 Apr;41(4):895-902. doi: 10.1109/TMI.2021.3126492. Epub 2022 Apr 1.
Dark-field radiography of the human chest is a promising novel imaging technique with the potential of becoming a valuable tool for the early diagnosis of chronic obstructive pulmonary disease and other diseases of the lung. The large field-of-view needed for clinical purposes could recently be achieved by a scanning system. While this approach overcomes the limited availability of large area grating structures, it also results in a prolonged image acquisition time, leading to concomitant motion artifacts caused by intrathoracic movements (e.g. the heartbeat). Here we report on a motion artifact reduction algorithm for a dark-field X-ray scanning system, and its successful evaluation in a simulated chest phantom and human in vivo chest X-ray dark-field data. By partitioning the acquired data into virtual scans with shortened acquisition time, such motion artifacts may be reduced or even fully avoided. Our results demonstrate that motion artifacts (e.g. induced by cardiac motion or diaphragmatic movements) can effectively be reduced, thus significantly improving the image quality of dark-field chest radiographs.
人体胸部的暗场射线照相术是一种很有前途的新型成像技术，有可能成为慢性阻塞性肺疾病和其他肺部疾病的早期诊断的有用工具。最近，一种扫描系统实现了临床应用所需的大视场。虽然这种方法克服了大面积光栅结构可用性有限的问题，但也导致图像采集时间延长，从而导致由胸腔内运动（例如心跳）引起的伴随运动伪影。在这里，我们报告了一种用于暗场 X 射线扫描系统的运动伪影减少算法，并在模拟胸部体模和人体体内胸部 X 射线暗场数据中成功进行了评估。通过将采集的数据分成缩短采集时间的虚拟扫描，可以减少甚至完全避免这种运动伪影。我们的结果表明，可以有效地减少运动伪影（例如由心脏运动或横膈膜运动引起的伪影），从而显著提高暗场胸部射线照相的图像质量。
